Optimizing the configuration of virtual machine instances in a networked computing environment

ABSTRACT

Embodiments of the present invention provide an approach for optimizing a configuration of virtual machine (VM) instances. In a typical embodiment, such optimization comprises either the splitting of a single VM instance into multiple VM instances or the consolidation of multiple VM instances into fewer (e.g., a single) VM instance. Along these lines, it will first be determined which VM instances would be good candidates for reconfiguration. Under one approach, VM instances that are candidates for reconfiguration are identified based upon an analysis of applicable/associated service level agreement (SLA) terms versus the performance of the VM instances. For example, VM instances can be reconfigured if such reconfiguration will maximize a benefit provided by the applicable SLA terms (e.g., if the splitting of a single VM instance into multiple VM instances would cause a workload to be processed more efficiently, resulting in a more favorable cost/benefit ratio). In another embodiment, candidate VM instances can be identified based upon a commonality of an entity (e.g., a consumer) associated therewith. For example, if a single entity is utilizing multiple VM instances, such VM instances could be considered candidates for consolidation to avoid unnecessary computing resource consumption.

TECHNICAL FIELD

The present invention relates generally to the optimization of virtualmachine (VM) instances. Specifically, the present invention relates tothe optimization of the configuration of VM instances in a networkedcomputing environment (e.g., a cloud computing environment).

BACKGROUND

The networked computing environment (e.g., cloud computing environment)is an enhancement to the predecessor grid environment, whereby multiplegrids and other computation resources may be further enhanced by one ormore additional abstraction layers (e.g., a cloud layer), thus makingdisparate devices appear to an end-consumer as a single pool of seamlessresources. These resources may include such things as physical orlogical computing engines, servers and devices, device memory, storagedevices, among others.

Within networked computing environments, it is often the case thatvirtual machines (VM) are utilized. In general, VM instances comprise atype of computing environment (e.g., a program or operating system) thatis based upon a software abstraction layer within a computing system. Inthis context, a VM instance is often called a “guest” while theenvironment in which it operates is called a “host.” VM instances aretypically created to execute a set of instructions different than thatof the host environment. Because VM instances are separated from thephysical resources they use, the host environment is often able todynamically assign those resources among the VM instances. Challengescan exist in that VM instances may be configured in a less than optimalfashion. For example, it could be the case that too many or too few VMinstances are provisioned within an environment. Such provisioning canresult in unnecessary consumption of computing resources, and/orinefficient processing of workloads.

SUMMARY

Embodiments of the present invention provide an approach for optimizinga configuration of virtual machine (VM) instances. In a typicalembodiment, such optimization comprises either the splitting of a singleVM instance into multiple VM instances or the consolidation of multipleVM instances into fewer (e.g., a single) VM instance. Along these lines,it will first be determined which VM instances would be good candidatesfor reconfiguration. Under one approach, VM instances that arecandidates for reconfiguration are identified based upon an analysis ofapplicable/associated service level agreement (SLA) terms versus theperformance of the VM instances. For example, VM instances can bereconfigured if such reconfiguration will maximize a benefit provided bythe applicable SLA terms (e.g., if the splitting of a single VM instanceinto multiple VM instances would cause a workload to be processed moreefficiently, resulting in a more favorable cost/benefit ratio). Inanother embodiment, candidate VM instances can be identified based upona commonality of an entity (e.g., a consumer) associated therewith. Forexample, if a single entity is utilizing multiple VM instances, such VMinstances could be considered candidates for consolidation to avoidunnecessary computing resource consumption.

A first aspect of the present invention provides a computer-implementedmethod for optimizing virtual machine instances in a networked computingenvironment, comprising: identifying a set of virtual machine (VM)instances in the networked computing environment that are potentialcandidates for optimization based upon at least one of the following: aperformance of the set of VM instances with respect to a set of servicelevel agreement (SLA) terms, or a commonality of an entity associatedwith the set of VM instances; and optimizing the set of VM instances byperforming at least one of the following actions: splitting a singleinstance of the set of VM instances into multiple instances, orconsolidating multiple instances of the set of VM instances into asingle instance.

A second aspect of the present invention provides a system foroptimizing virtual machine instances in a networked computingenvironment, comprising: a bus; a processor coupled to the bus; and amemory medium coupled to the bus, the memory medium comprisinginstructions to: identify a set of virtual machine (VM) instances in thenetworked computing environment that are potential candidates foroptimization based upon at least one of the following: a performance ofthe set of VM instances with respect to a set of service level agreement(SLA) terms, or a commonality of an entity associated with the set of VMinstances; and optimize the set of VM instances by performing at leastone of the following actions: splitting a single instance of the set ofVM instances into multiple instances, or consolidating multipleinstances of the set of VM instances into a single instance.

A third aspect of the present invention provides a computer programproduct for optimizing virtual machine instances in a networkedcomputing environment, the computer program product comprising acomputer readable storage media, and program instructions stored on thecomputer readable storage media, to: identify a set of virtual machine(VM) instances in the networked computing environment that are potentialcandidates for optimization based upon at least one of the following: aperformance of the set of VM instances with respect to a set of servicelevel agreement (SLA) terms, or a commonality of an entity associatedwith the set of VM instances; and optimize the set VM instances byperforming at least one of the following actions: splitting a singleinstance of the set of VM instances into multiple instances, orconsolidating multiple instances of the set of VM instances into asingle instance.

A fourth aspect of the present invention provides a method for deployinga system for optimizing virtual machine instances in a networkedcomputing environment, comprising: providing a computer infrastructurebeing operable to: identify a set of virtual machine (VM) instances inthe networked computing environment that are potential candidates foroptimization based upon at least one of the following: a performance ofthe set of VM instances with respect to a set of service level agreement(SLA) terms, or a commonality of an entity associated with the set of VMinstances; and optimize the set VM instances by performing at least oneof the following actions: splitting a single instance of the set of VMinstances into multiple instances, or consolidating multiple instancesof the set of VM instances into a single instance.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features of this invention will be more readilyunderstood from the following detailed description of the variousaspects of the invention taken in conjunction with the accompanyingdrawings in which:

FIG. 1 depicts a cloud computing node according to an embodiment of thepresent invention.

FIG. 2 depicts a cloud computing environment according to an embodimentof the present invention.

FIG. 3 depicts abstraction model layers according to an embodiment ofthe present invention.

FIG. 4 depicts a system diagram according to an embodiment of thepresent invention.

FIG. 5 depicts an illustrative user interface for VM instanceconfiguration according to an embodiment of the present invention.

FIG. 6 depicts an illustrative block diagram showing the movement of aproject pursuant to a consolidation operation according to an embodimentof the present invention.

FIG. 7 depicts an internet protocol (IP) configuration prior to aconsolidation operation according to an embodiment of the presentinvention.

FIG. 8 depicts an internet protocol (IP) configuration after aconsolidation operation according to an embodiment of the presentinvention.

FIG. 9 depicts a process flow diagram according to an embodiment of thepresent invention.

FIG. 10 depicts a database (DB) configuration before service connectionsare updated using a direct method according to an embodiment of thepresent invention.

FIG. 11 depicts a database (DB) configuration after service connectionsare updated using the direct method according to an embodiment of thepresent invention.

FIG. 12 depicts a database (DB) configuration before service connectionsare updated using a proxy method according to an embodiment of thepresent invention.

FIG. 13 depicts a database (DB) configuration after service connectionsare updated using the proxy method according to an embodiment of thepresent invention.

FIG. 14 depicts a method flow diagram according to an embodiment of thepresent invention.

The drawings are not necessarily to scale. The drawings are merelyschematic representations, not intended to portray specific parametersof the invention. The drawings are intended to depict only typicalembodiments of the invention, and therefore should not be considered aslimiting the scope of the invention. In the drawings, like numberingrepresents like elements.

DETAILED DESCRIPTION

Illustrative embodiments now will be described more fully herein withreference to the accompanying drawings, in which exemplary embodimentsare shown. This disclosure may, however, be embodied in many differentforms and should not be construed as limited to the exemplaryembodiments set forth herein. Rather, these exemplary embodiments areprovided so that this disclosure will be thorough and complete and willfully convey the scope of this disclosure to those skilled in the art.In the description, details of well-known features and techniques may beomitted to avoid unnecessarily obscuring the presented embodiments.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of this disclosure.As used herein, the singular forms “a”, “an”, and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. Furthermore, the use of the terms “a”, “an”, etc., do notdenote a limitation of quantity, but rather denote the presence of atleast one of the referenced items. It will be further understood thatthe terms “comprises” and/or “comprising”, or “includes” and/or“including”, when used in this specification, specify the presence ofstated features, regions, integers, steps, operations, elements, and/orcomponents, but do not preclude the presence or addition of one or moreother features, regions, integers, steps, operations, elements,components, and/or groups thereof.

SUMMARY

Embodiments of the present invention provide an approach for optimizinga configuration of virtual machine (VM) instances. In a typicalembodiment, such optimization comprises either the splitting of a singleVM instance into multiple VM instances or the consolidation of multipleVM instances into fewer (e.g., a single) VM instance. Along these lines,it will first be determined which VM instances would be good candidatesfor reconfiguration. Under one approach, VM instances that arecandidates for reconfiguration are identified based upon an analysis ofapplicable/associated service level agreement (SLA) terms versus theperformance of the VM instances. For example, VM instances can bereconfigured if such reconfiguration will maximize a benefit provided bythe applicable SLA terms (e.g., if the splitting of a single VM instanceinto multiple VM instances would cause a workload to be processed moreefficiently, resulting in a more favorable cost/benefit ratio). Inanother embodiment, candidate VM instances can be identified based upona commonality of an entity (e.g., a consumer) associated therewith. Forexample, if a single entity is utilizing multiple VM instances, such VMinstances could be considered candidates for consolidation to avoidunnecessary computing resource consumption.

It is understood in advance that although this disclosure includes adetailed description of cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded, automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active consumer accounts). Resource usage canbe monitored, controlled, and reported providing transparency for boththe provider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based email). Theconsumer does not manage or control the underlying cloud infrastructureincluding network, servers, operating systems, storage, or evenindividual application capabilities, with the possible exception oflimited consumer-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication-hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 1, a schematic of an example of a cloud computingnode is shown. Cloud computing node 10 is only one example of a suitablecloud computing node and is not intended to suggest any limitation as tothe scope of use or functionality of embodiments of the inventiondescribed herein. Regardless, cloud computing node 10 is capable ofbeing implemented and/or performing any of the functionality set forthhereinabove.

In cloud computing node 10, there is a computer system/server 12, whichis operational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with computer system/server 12 include, but are notlimited to, personal computer systems, server computer systems, thinclients, thick clients, hand-held or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

Computer system/server 12 may be described in the general context ofcomputer system-executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 12 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 1, computer system/server 12 in cloud computing node 10is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 12 may include, but are not limitedto, one or more processors or processing units 16, a system memory 28,and a bus 18 that couples various system components including systemmemory 28 to processor 16.

Bus 18 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnects (PCI) bus.

Computer system/server 12 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 12, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 28 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 30 and/or cachememory 32. Computer system/server 12 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 34 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM, or other optical media can be provided.In such instances, each can be connected to bus 18 by one or more datamedia interfaces. As will be further depicted and described below,memory 28 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions of embodiments of the invention.

The embodiments of the invention may be implemented as a computerreadable signal medium, which may include a propagated data signal withcomputer readable program code embodied therein (e.g., in baseband or aspart of a carrier wave). Such a propagated signal may take any of avariety of forms including, but not limited to, electro-magnetic,optical, or any suitable combination thereof. A computer readable signalmedium may be any computer readable medium that is not a computerreadable storage medium and that can communicate, propagate, ortransport a program for use by or in connection with an instructionexecution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium including, but not limited to, wireless,wireline, optical fiber cable, radio-frequency (RF), etc., or anysuitable combination of the foregoing.

Program/utility 40, having a set (at least one) of program modules 42,may be stored in memory 28 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 42 generally carry out the functions and/ormethodologies of embodiments of the invention as described herein.

Computer system/server 12 may also communicate with one or more externaldevices 14 such as a keyboard, a pointing device, a display 24, etc.;one or more devices that enable a consumer to interact with computersystem/server 12; and/or any devices (e.g., network card, modem, etc.)that enable computer system/server 12 to communicate with one or moreother computing devices. Such communication can occur via I/O interfaces22. Still yet, computer system/server 12 can communicate with one ormore networks such as a local area network (LAN), a general wide areanetwork (WAN), and/or a public network (e.g., the Internet) via networkadapter 20. As depicted, network adapter 20 communicates with the othercomponents of computer system/server 12 via bus 18. It should beunderstood that although not shown, other hardware and/or softwarecomponents could be used in conjunction with computer system/server 12.Examples include, but are not limited to: microcode, device drivers,redundant processing units, external disk drive arrays, RAID systems,tape drives, and data archival storage systems, etc.

Referring now to FIG. 2, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 comprises one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as private, community,public, or hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms, and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 2 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 3, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 2) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 3 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include mainframes. In oneexample, IBM® zSeries® systems and RISC (Reduced Instruction SetComputer) architecture based servers. In one example, IBM pSeries®systems, IBM xSeries® systems, IBM BladeCenter® systems, storagedevices, networks, and networking components. Examples of softwarecomponents include network application server software. In one example,IBM WebSphere® application server software and database software. In oneexample, IBM DB2® database software. (IBM, zSeries, pSeries, xSeries,BladeCenter, WebSphere, and DB2 are trademarks of International BusinessMachines Corporation registered in many jurisdictions worldwide.)

Virtualization layer 62 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers;virtual storage; virtual networks, including virtual private networks;virtual applications and operating systems; and virtual clients.

In one example, management layer 64 may provide the functions describedbelow. Resource provisioning provides dynamic procurement of computingresources and other resources that are utilized to perform tasks withinthe cloud computing environment. Metering and pricing provide costtracking as resources are utilized within the cloud computingenvironment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.Consumer portal provides access to the cloud computing environment forconsumers and system administrators. Service level management providescloud computing resource allocation and management such that requiredservice levels are met. Service Level Agreement (SLA) planning andfulfillment provides prearrangement for, and procurement of, cloudcomputing resources for which a future requirement is anticipated inaccordance with an SLA. Further shown in management layer is VM instanceoptimization, which represents the functionality that is provided underthe embodiments of the present invention.

Workloads layer 66 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation; software development and lifecycle management; virtualclassroom education delivery; data analytics processing; transactionprocessing; and consumer data storage and backup. As mentioned above,all of the foregoing examples described with respect to FIG. 3 areillustrative only, and the invention is not limited to these examples.

It is understood that all functions of the present invention asdescribed herein typically may be performed by the VM instanceoptimization functionality (of management layer 64, which can betangibly embodied as modules of program code 42 of program/utility 40(FIG. 1). However, this need not be the case. Rather, the functionalityrecited herein could be carried out/implemented and/or enabled by any ofthe layers 60-66 shown in FIG. 3.

It is reiterated that although this disclosure includes a detaileddescription on cloud computing, implementation of the teachings recitedherein are not limited to a cloud computing environment. Rather, theembodiments of the present invention are intended to be implemented withany type of networked computing environment now known or laterdeveloped.

Referring to FIG. 4, the approach provided under the embodiments of thepresent invention is depicted. Specifically, FIG. 4 represents a systemdiagram showing a process in which a VM instance optimization system 80that provides VM instance configuration/reconfiguration. In a typicalembodiment, VM instance optimization system 80 comprises one or moresoftware programs/utilities such as program 40 of FIG. 1 that enablesthe functionality discussed herein and that is represented by the VMinstance optimization function of management layer 64 of FIG. 3. Alongthese lines, VM instance optimization system 80 can comprise a rulesengine or the like that is configured to split a single VM instance 82into multiple VM instances 84 and/or consolidate multiple VM instances86 into fewer (e.g., a single) VM instance 88. As will be furtherdescribed below, such determinations can be made based upon one or morefactors such as SLA terms 90 associated with the VM instances and/orcommonality of entities 92 associated with the VM instances. It isunderstood in advance that the section headings that appear below areutilized for ease of reading purposes only and are not intended toindicate a particular relevance of one section over another.

Identification of Reconfiguration Opportunities

The following describes two methods to determine opportunities toreconfigure (e.g., consolidate and/or split) service VM instances of thesame VM instances template type. Service VM instances are defined as VMinstances which host generic services such as a database or middleware.The following criteria are indicative of good VM instance candidates tobe reconfigured.

-   -   1) The VM instances are operating on average below the SLA (say        using less than 50% of the requested resources) but have        periodic spikes of resource usage. The user still needs to        maintain the large SLA for peak usage but can consolidate these        like-VM instances together since peaks will most likely not        coincide.    -   2) The VM instances are primarily managed by the same        individual. One way this can be determined is if the VM        instances being accessed mostly come from the same IP address.        If the same individual is managing multiple services, combining        these like-VM instances together reduces the number of instances        that must be maintained.

Consolidation Opportunities

When these similar criteria are observed, then the VM instances shouldbe selected for reconfiguration. The following two algorithms determinegood consolidation candidates based on the two previously mentionedexamples of consolidation criteria.

Determination Algorithm 1: Selecting Consolidation Candidates Using SLA

-   -   1. For each customer c do:    -   2. For each VM instances Template t which has at least one        currently provisioned instance do:    -   3. candidateList=[ ]    -   4. for each instance i for template t do:    -   5. if max usage of VM instance i is <50% of SLA do:    -   6. candidateList.append(i)

Determination Algorithm 2: Selecting Consolidation Candidates Using SameAccess ID

Function Prototype/Description:

-   -   get Majority Access ID(VM instance i)—This method determines an        ID (be it IP address or login name or some other identifier)        which is primarily accessing VM instance i. If no one ID has        over 50% of the accesses, then null is returned.

Algorithm Steps:

-   -   1. for each customer c do:    -   2. for each VM instances Template t which has at least two        currently provisioned instance do:    -   3. candidateGroups=HashMap<String,List>    -   4. for each instance i for template t do:    -   5. MainID=getMajority AccessID(i)    -   6. If mainID==null do:    -   7. Continue    -   8. cg=consolidationGroups.get(mainID)    -   9. if cg==null do:    -   10. new consolidation List=[i]    -   11. consolidationGroups.put(mainID,newconsolidationList)    -   12. else:    -   13. cg.append(i)    -   14.    -   15. finalCandidateGroups=[ ]    -   16. for candidate group list cgl in candidateGroups do:    -   17. if cgl.length>=2 do:    -   18. finalCandidateGroups.append(cgl)        Once a list of the good consolidation candidates has been        determined, these candidates can be presented to the consumer        for consideration, consumer authorization may be requested        before consolidation because the consolidation process allows        partial VM instances access between projects which may be an        unwanted security threat.

Split Opportunities

In addition to determining when a VM instance should be consolidated,there are times when a service VM instance should be split into multipleservice VM instances. This should be done in scenarios where high-valuecustomers have demanding SLA agreements and their associated service VMinstances are close to its maximum usage. For example, say project 1 andproject 2 were consolidated and project 2 had a high-value SLA. Considerthe possibility that the average load of the consolidated service VMinstances are >90% of the SLA. Since project 2 has a high-value SLAwhich must be maintained, it is safer to now separate the VM instancesinto their own service VM instances. The algorithm to determine splitcandidates can be found below:

Determination Algorithm 3: Selecting Split Candidates Using SLA

-   -   1. For each customer c do:    -   2. candidateList=[ ]    -   3. for each service VM instance i which contains multiple        service do:    -   4. if max usage of i is >90% of SLA do:    -   5. candidateList.append(i)

Referring to FIG. 5, an illustrative interface 100 for reconfiguring

VM instances is shown. It is understood in advance that although FIG. 5depicts a VM instance consolidation operation, a similar interface canbe presented for a VM instance split operation. As depicted, interface100 comprises: a candidate area 102 for listing VM instances that have apotential to be consolidated; a selection area 104 for selecting VMinstances to be consolidated; an VM instance addition area 106 forrequesting new VM instances, and an action mechanism 108, the selectionof which will cause VM instances selected via selection area 104 to beconsolidated.

Reconfiguration Algorithm

This section described the process that occurs once VM instancecandidates have been identified and/or selected. Specifically, thefollowing are the steps in the general consolidation/split (collectivelyreferred to as reconfiguration) algorithm:

-   -   1. Update Network Configuration (either 1) internal project        or 2) separate resource pool)    -   2. Create Resources (used only in the split process)    -   3. Move Services (implementation defined by the ISV image        provider)    -   4. Update Service Pointers (via 1) topology info update, 2)        proxy update, or 3) IP update)    -   5. Delete Unused Resources (used only in the consolidation        process)        Resources: e.g., VM instances which contain any number of        services of the same type        Services: e.g., DB2 database services or Websphere Application        Server (WAS) services

Step 1—Update Network Configuration:

This initial step configures a firewall with the appropriate Virtuallocal Area Network (VLAN) and IP/port information. Depending on thelevel of required security two methods can be employed:

-   -   1. Keep the main consolidated VM instances in the project        security zone. This method is particularly useful (among other        situations) when the projects sharing resources can be trusted        among themselves. This is typically the case since the service        consolidation scope will usually be limited to one cloud        consumer.    -   2. Pull the consolidated VM instances into a pool security zone        which is independent of any projects. This is more secure since        it does not allow a project direct access to the VM instances in        another project. An example of this is shown in FIG. 6. As        depicted, a domain 110 is shown in which two projects 112A-B are        being performed. Each project has VM instances 114A-N. As        further, rather than each project leverage its own project        database (DB) 118 and 120, a consolidated resource pool 116 is        created hereunder having the needed project DB 118 that both        projects 112A-B can leverage. This avoids both projects from        needing separate DBs.

Step 2—Create Resources:

This step is only needed during the split process to create additionalVM instances resources. This step creates new service VM instances ofthe same type which will contain at least one of the services after thesplit process has been completed.

Step 3—Move Services:

Once the resources and the necessary network configuration are complete,the VM instance optimization 80 can start the consolidation/splitprocess. This involves calling the

Instance1.incorportateServicesRunningOn (instance 2);

step as defined in the main disclosure for consolidation or the

Instance1.splitServicesOnto (instance 2);

step for the split process. How to choose which instance should bewhich, and which service(s) to split will be further discussed below.

Step 4—Update Service Pointers:

There are a number of ways to update the pointers to the resource VMinstances after the consolidation/splitting has taken place. The firsttwo were introduced hereinabove, but a more advanced update process isdescribed as well.

-   -   1. Topology Information: This method uses topology information        which was retained from the initial project deployment to know        directly which pointers need to be updated. For instance, when        project 2's VM instance1 and VM instances are provisioned, the        cloud system knows that they are connected to Project 2's DB        instance. When a consolidation/split occurs, this connection        information is retrieved and used to update the connections to        point to the new consolidated/split VM instances.    -   2. Proxy Instance: This method uses one proxy server for each        cloud consumer in order to serve as an intermediary. The proxy        can be configured either as a Domain Name Server (DNS) type        service or as a direct data pass through. One difference is that        the direct pass through is more secure since it does not allow        direct project-to-project access, but it does require a scaling        implementation if lots of data is being passed through the        proxy.    -   3. Service IP addresses: This method uses the concept of service        IP addresses in order to change the links between service VM        instances. In order to change the links between two VM        instances, the IP address of the old service VM instances are        adopted by the consolidated VM instances. FIGS. 7 and 8 depict a        before and after process for updating service pointers based on        the domain 110, project 112A-B, and VM instances 114A-N shown in        FIG. 6. As depicted first in FIG. 7, the VM instances 114A-N in        respective projects 112A-B each point to their own project DB        118 and 120, respectively. Under the teachings recited herein,        the service pointers can be changed so that the service pointers        for each VM instance 114A-N point to a common project DB 118, as        shown in FIG. 8. In general, this involves changing the target        IP address.

During the split process, the service IP method can only split servicesgrouped under different IP addresses. That is, a prior consolidationcould be necessary for a split to occur since consolidation is the onlyway for a service VM instance to have multiple IP addresses. This is nottypically an issue since a majority of splits occur when a consolidatedservice VM instance outgrows its current capacity.

Step 5—Delete Unused Resources:

The final step is to delete any resources which are no longer required.This step is only applicable in a consolidation scenario where a VMinstance has been completely consolidated into another service VMinstance and is no longer running any services.

Determining which Services to Move to which Locations

While it has been described above how to determine which services areconsolidation/split candidates, this section will discuss how it isdetermined which VM instances should be maintained for consolidationsand which services should be separated during the split processes.

Consolidation

1. Choose the consolidation path which will take the least amount oftime. This method used the following function:

instance1.timeToConsolidateServices( )

which would be a part of the Independent Software Vendor (ISV) imageprovider's interface Application Programming Interface (API). Thisfunction could then again be called on instance2 which would give therelative amount of time to consolidate instance2 into another VMinstances. The algorithm then chooses the VM instances which would takethe most time to consolidate. This results in minimizing the overallmove time since the services which take the longest time to consolidatewill not be moved. The following is an algorithm describing how tochoose a consolidation path that will take the least amount of time:

-   -   1. for each candidate VM instance i to consolidate do:    -   2. mostTimeToConsolidate=null    -   3. if mostTimeToConsolidate==null ∥    -   4. mostTimeToConsolidate.timeToConsolidateService(        )LtimeToConsolid ateService( )o    -   5. mostTimeToConsolidate=i

Splitting

1. Choose the service(s) which require the lesser amount of time tomove. This method looks through all of the services on the VM instancesto be split and selects the service which requires the least time tomove via the

instanceToSplit.timeToSplit (Services)

method. The timeToSplit( )method would be a relative time and would beimplemented by the ISV image provider. This method can also beconfigured to move a given percentage of the services with the leastmove time (e.g. split 30% of the total number of services and move theones which take the least time to move).

The following is an algorithm describing how to minimize split time:

1. For each servicein a VM instance i to be split do:2. leastTimeToSplit=null3. if leastTimeToSplit==null ∥

4. LtimeToSplit(s)<LtimeToSplit(leastTimeToSplit) do:

5. leastTimeToSplit=s

2. Choose the service(s) which holds the higher-value SLAs. This methodlooks through all of the services on the VM instances and chooses theservice which is associated with the highest-value SLA via the

instanceToSplit.valueOfSLA (service s)

method. By separating the highest-value SLA into a separate VM instance,it will be easier for the VM instance optimization system to maintainthat SLA. This method can be configured to split off a given percentageof the high-value SLA services (e.g. split 30% of the total number ofservices and move the ones with the highest-value SLA). The following isan algorithm describing how to split the VM instance having the highestvalue SLA (maximize the reward):

1. for each service in a VM instance i to be split do:

2. mostHighValueSLA=null

3. if mostHighValueSLA==null ∥

4. i.valueOfSLA(s)>i.valueOfSLA (mostHighValueSLA) do:

5. mostHighValueSLA=s

One noteworthy property of the previously disclosed consolidation/splitalgorithm is that it can occur automatically. That is, at any pointduring the consolidation/split process, the entire cloud can be revertedto the state before the consolidation/split was initiated. This isnoteworthy since it prevents the cloud from becoming inconsistent due tofailures. For example, assume that the consolidation/split processfailed midway through the update service pointers step and the algorithmwas not atomic. Under such a scenario, there would be VM instancescommunicating to both new and old service VM instances which wouldresult in data loss. However, when the consolidation/split process failswith atomicity, the cloud is reverted to the state before theconsolidation/split occurred. Thus, preventing any inconsistencies.

In addition, under the embodiments recited herein, VM instances can bepooled. Service VM instances consolidations can incorporate the conceptsof SLA terms in two distinct ways, each with their own benefits. Underone method, VM instances with differing SLA terms are pooled into thesame service VM instances pool. This method groups VM instances intoservice VM instances pools with differing SLA terms. The idea is thathigh-value SLA VM instances would be able to consume the lower-value SLAVM instances' resources within the same pool as needed. When thehigh-value SLA VM instances do not require the resources however, thelower-value SLA VM instances would be free to use those resourceswithout interfering with the high-value SLA VM instances. Under analternate method, VM instances with similar SLA terms can be pooled intothe same service VM instances pool. This latter method keeps alllow-value SLA VM instances in the same service VM instances pool and allhigh-value SLA VM instances in another. By doing this, a cloudmanagement system would be able to direct the majority of its resourcesto the high-value SLA service VM instances pool while the low-value SLApools could have lower priority.

To increase the security while using a proxy configuration, deep packetinspections can be used in order to ensure port misuse does not occur.For instance, when DB2 VM instances are being consolidated, DB2 trafficmust be passed through the proxy server to the VM instances where thoseservices will now be available. As all access to those services will bethrough the proxy, deep packet inspection can be used to verify that thedata being transmitted back and forth is reasonable under the assumptionthat the packets are DB2 traffic.

Illustrative Example

This section will utilize the above-referenced teachings within theconfines of a consolidation operation. It is understood that a similarprocess could be utilized for a splitting operation. In this example,once a consumer (e.g., a cloud consumer) decides which VM instances toconsolidate, the consolidation process can begin. It is further notedthat this consolidation algorithm utilizes a consolidation service toexist in a virtual image template which can then be used by the cloudmanagement software to do the following.

VM instancesTemplateInstance Instance1;

VM instancesTemplateInstance instance2;

Instance1.incorportateServicesRunningOn (instance2).

This functionality can be implemented through a service on a particularport of the VM instance which will take another instance of the sametype's access information such as IP address and password. With thisinformation, all the services running on instance 2 will, afterconsolidation, be running on instance 1. The cloud will then be able todelete instance 2 as all services are now provided on instance 1. Itwill be in the best interest of the cloud image provider to implementthis consolidation API since images which do will be more attractive tocloud consumers because of the increased consolidation flexibility.

FIG. 9 depicts a process flow diagram 200 showing an overview of theconsolidation process/operation. As shown, “holes” are opened to allowVM instance 1 to access VM instance 2 and vice versa. Thereafter,credentials associated with VM instance 2 are provided to VM instance 1.Next, service information is requested and corresponding service datareturned to VM instance 2. At this point the consolidation is completeand VM instance 1 is now connected to VM instance 2, and VM instance 2is updated with credentials associated with VM instance 1. Lastly, theconsolidated VM instance (e.g., VM instance 2) is deleted.

Before the consolidation algorithm is explained in greater detail, anexplanation will be given for the “Update Service Connections” (e.g.,step 3). Specifically, there are at least two implementations for step3. The first is a straightforward direct update of all the existingservice connections using the provisioning topology. The second,however, requires that a customer-wide proxy be used for each type ofservice VM instances. The proxy VM instances act similar to a DNSdirectory for accessing services. While this may result in increasedoverhead with the extra VM instances, it enables simpler consolidationand enables consolidation in environments where the originalprovisioning topology is not accessible. The following algorithmdescribes how to consolidate VM instances using the aforementioneddirect and proxy methods.

Inputs:

-   -   1. VM instance 1=The VM instances which will host all service        after the consolidation.    -   2. VM instance 2=the VM instances whose services will be        transferred to VM instances 1.

Algorithm Steps:

-   -   1. Open selective access between projects: Since VM instances 1        will need to access VM instances 2 and the VM instances in VM        instances 2's project will now need to talk to VM instances 1, a        pinhole must be opened between the VLANs to allow for        cross-communication. This can be done by configuring the        networking firewalls in a similar way to when the VLANS are set        up initially. (Note: this step is not necessary if VM instances        1 and VM instances 2 are in the same project.)    -   2. Copy VM instances 2's service into VM instances 1: From the        Cloud Management software, connect to VM instances) on the        consolidation service listening on a specified VM instances 1        port. Over this connection, provide the necessary information        for VM instances 1 to log into VM instances 2. This will        initiate the service consolidation code written by the image        provider to connect to VM instances 2 and pull/propagate over        all information necessary to continue VM instances 2's services        on VM instances 1. This consolidation process may include        increasing VM instances 1's resources to accommodate VM        instances 2's services.    -   3. a) Update service connections (direct connection): Since the        VM instances in VM instances 2's project have access to VM        instances 1 via the previously opened pinholes, all the service        connections can now be updated. Using a topological approach        (e.g., Zepher) which was used to create VM instances 2's        project, obtain a list of VM instances which are connected to VM        instances 2. Rerun the initial configuration workflow for each        of these VM instances and pass the access information for VM        instances 1. This update will change all VM instances 2 pointers        to VM instances 1 instead. An example of the direct connection        approach is shown in FIGS. 10-11. Both Figs. show domain 110,        projects 112A-B, VM instances 114A-N, and project DBs 118 and        120. In FIG. 10, each VM instance 114A-N is connected to a        project DB 118 and 120 within the project 112A-B with which the        VM instances 114A-N are associated. In FIG. 11, the VM instances        114C-N in project 112B are disconnected from project DB 120 and        instead directly connected to project DB 118 in project 114A.        -   b) Update service connections (proxy connection):            Alternatively, updating service connections in the situation            where a customer-wide service proxy exists can be readily            performed. The cloud management software can log into the            service proxy and change all the VM instances 2 references            to VM instances 1. Therefore the next time any VM instances            in VM instances 2's project resolves the service location            with the proxy, they will then be directed to VM instances            1. An example of the proxy connection approach is shown in            FIGS. 12-13. Both Figs. shown domain 110, projects 112A-B,            VM instances 114A-N, project DBs 118 and 120, and DB2 proxy            122. In FIG. 12, each VM instance 114A-N is connected to DB2            proxy 122, which in turn is connected to both project DBs            118 and 120. Conversely, in FIG. 13, DB2 proxy 122 is            coupled only to project DB 118 (DB2® is a trademark of IBM            Corp in the United States and/or other countries).    -   4. Delete VM instances 2: Once all the services previously        running on VM instances 2 have been transferred over to VM        instances 1 and all VM instances 2 pointers have been changed,        VM instances 2 can safely be deleted.

Referring now to FIG. 14, a method flow diagram according to anembodiment of the present invention is shown. After the processes isstarted in step S1, it is determined in step S2 whether a set of VMinstances will identifying based upon a performance of the set of VMinstances with respect to a set of service level agreement (SLA) terms.If not, the set of VM instances will be identified based upon acommonality of an entity associated with the set of VM instances in stepS3. In either event, once the set of VM instances that are candidatesfor optimization (e.g., reconfiguration) are identified, it will bedetermined in step S4 whether the optimization of the set of VMinstances will occur via a consolidation operation. If so, the set of VMinstances are consolidated in step S5 before the processes is ended instep S7. However, if consolidation operation does not occur,optimization will occur via a split operation in step S6 before theprocess is ended in step S7.

While shown and described herein as a VM instance optimization solution,it is understood that the invention further provides various alternativeembodiments. For example, in one embodiment, the invention provides acomputer-readable/useable medium that includes computer program code toenable a computer infrastructure to provide VM instance optimizationfunctionality as discussed herein. To this extent, thecomputer-readable/useable medium includes program code that implementseach of the various processes of the invention. It is understood thatthe terms computer-readable medium or computer-useable medium compriseone or more of any type of physical embodiment of the program code. Inparticular, the computer-readable/useable medium can comprise programcode embodied on one or more portable storage articles of manufacture(e.g., a compact disc, a magnetic disk, a tape, etc.), on one or moredata storage portions of a computing device, such as memory 28 (FIG. 1)and/or storage system 34 (FIG. 1) (e.g., a fixed disk, a read-onlymemory, a random access memory, a cache memory, etc.).

In another embodiment, the invention provides a method that performs theprocess of the invention on a subscription, advertising, and/or feebasis. That is, a service provider, such as a Solution Integrator, couldoffer to provide VM instance optimization functionality. In this case,the service provider can create, maintain, support, etc., a computerinfrastructure, such as computer system 12 (FIG. 1) that performs theprocesses of the invention for one or more consumers. In return, theservice provider can receive payment from the consumer(s) under asubscription and/or fee agreement and/or the service provider canreceive payment from the sale of advertising content to one or morethird parties.

In still another embodiment, the invention provides acomputer-implemented method for VM instance optimization. In this case,a computer infrastructure, such as computer system 12 (FIG. 1), can beprovided and one or more systems for performing the processes of theinvention can be obtained (e.g., created, purchased, used, modified,etc.) and deployed to the computer infrastructure. To this extent, thedeployment of a system can comprise one or more of: (1) installingprogram code on a computing device, such as computer system 12 (FIG. 1),from a computer-readable medium; (2) adding one or more computingdevices to the computer infrastructure; and (3) incorporating and/ormodifying one or more existing systems of the computer infrastructure toenable the computer infrastructure to perform the processes of theinvention.

As used herein, it is understood that the terms “program code” and“computer program code” are synonymous and mean any expression, in anylanguage, code, or notation, of a set of instructions intended to causea computing device having an information processing capability toperform a particular function either directly or after either or both ofthe following: (a) conversion to another language, code, or notation;and/or (b) reproduction in a different material form. To this extent,program code can be embodied as one or more of: an application/softwareprogram, component software/a library of functions, an operating system,a basic device system/driver for a particular computing device, and thelike.

A data processing system suitable for storing and/or executing programcode can be provided hereunder and can include at least one processorcommunicatively coupled, directly or indirectly, to memory elementsthrough a system bus. The memory elements can include, but are notlimited to, local memory employed during actual execution of the programcode, bulk storage, and cache memories that provide temporary storage ofat least some program code in order to reduce the number of times codemust be retrieved from bulk storage during execution. Input/outputand/or other external devices (including, but not limited to, keyboards,displays, pointing devices, etc.) can be coupled to the system eitherdirectly or through intervening device controllers.

Network adapters also may be coupled to the system to enable the dataprocessing system to become coupled to other data processing systems,remote printers, storage devices, and/or the like, through anycombination of intervening private or public networks. Illustrativenetwork adapters include, but are not limited to, modems, cable modems,and Ethernet cards.

The foregoing description of various aspects of the invention has beenpresented for purposes of illustration and description. It is notintended to be exhaustive or to limit the invention to the precise formdisclosed and, obviously, many modifications and variations arepossible. Such modifications and variations that may be apparent to aperson skilled in the art are intended to be included within the scopeof the invention as defined by the accompanying claims.

1. A computer-implemented method for optimizing virtual machineinstances in a networked computing environment, comprising: identifyinga set of virtual machine (VM) instances in the networked computingenvironment that are potential candidates for optimization based upon atleast one of the following: a performance of the set of VM instanceswith respect to a set of service level agreement (SLA) terms, or acommonality of an entity associated with the set of VM instances; andoptimizing the set of VM instances by performing at least one of thefollowing actions: splitting a single instance of the set of VMinstances into multiple instances, or consolidating multiple instancesof the set of VM instances into a single instance.
 2. Thecomputer-implemented method of claim 1, the identifying comprisingdetermining whether an actual usage of the set of VM instances are belowa predefined threshold as compared to a target usage as set forth in theset of SLA terms.
 3. The computer-implemented method of claim 1, theidentifying comprising comparing a user identification corresponding toeach of the set of VM instances to one another.
 4. Thecomputer-implemented method of claim 1, the consolidating comprising:establishing communication between a first instance and a secondinstance of the set of VM instances; providing credentials associatedwith the second instance to the first instance; and deleting the secondinstance.
 5. The computer-implemented method of claim 1, the splittingcomprising: generating, responsive to an existence of a first instanceof the set of VM instances, a second instance to correspond to a firstinstance of the set of VM instances; establishing communication betweenthe first instance and the second instance; and copying a set ofcredentials associated the first instance to the second instance.
 6. Thecomputer-implemented method of claim 1, the optimizing comprising:updating a network configuration associated with the set of VMinstances; moving a set of services associated with the set of VMinstances; updating a set of service pointers associated with the set ofservices; and deleting a set of unused resources.
 7. Thecomputer-implemented method of claim 6, further comprising creating aset of resources in the event the optimizing comprises splitting.
 8. Thecomputer-implemented method of claim 6, the moving comprising:identifying the set of services; and determining at least one locationto move the set of services.
 9. The computer-implemented method of claim8, the set of services being identified based upon at least one of thefollowing: a minimization of a time needed to perform the identifying,or a maximization of at least one benefit associated with the set of SLAterms.
 10. A system for optimizing virtual machine instances in anetworked computing environment, comprising: a bus; a processor coupledto the bus; and a memory medium coupled to the bus, the memory mediumcomprising instructions to: identify a set of virtual machine (VM)instances in the networked computing environment that are potentialcandidates for optimization based upon at least one of the following: aperformance of the set of VM instances with respect to a set of servicelevel agreement (SLA) terms, or a commonality of an entity associatedwith the set of VM instances; and optimize the set of VM instances byperforming at least one of the following actions: splitting a singleinstance of the set of VM instances into multiple instances, orconsolidating multiple instances of the set of VM instances into asingle instance.
 11. The system of claim 10, the memory medium furthercomprising instructions to determine whether an actual usage of the setof VM instances is below a predefined threshold as compared to a targetusage as set forth in the set of SLA terms.
 12. The system of claim 10,the memory medium further comprising instructions to compare a useridentification corresponding to each of the set of VM instances to oneanother.
 13. The system of claim 10, the memory medium furthercomprising instructions to: establish communication between a firstinstance and a second instance of the set of VM instances; providecredentials associated with the second instance to the first instance;and delete the second instance.
 14. The system of claim 10, the memorymedium further comprising instructions to: generate, responsive to anexistence of a first instance of the set of VM instances, a secondinstance to correspond to a first instance of the set of VM instances;establish communication between the first instance and the secondinstance; and copy a set of credentials associated with the firstinstance to the second instance.
 15. The system of claim 10, the memorymedium further comprising instructions to: update a networkconfiguration associated with the set of VM instances; move a set ofservices associated with the set of VM instances; update a set ofservice pointers associated with the set of services; and delete a setof unused resources.
 16. The system of claim 15, the memory mediumfurther comprising instructions to create a set of resources in theevent the optimizing comprises splitting.
 17. The system of claim 15,the memory medium further comprising instructions to: identify the setof services; and determine at least one location to move the set ofservices.
 18. The system of claim 17, the set of services beingidentified based upon at least one of the following: a minimization of atime needed to perform the identifying, or a maximization of at leastone benefit associated with the set of SLA terms.
 19. A computer programproduct for optimizing virtual machine instances in a networkedcomputing environment, the computer program product comprising acomputer readable storage media, and program instructions stored on thecomputer readable storage media, to: identify a set of virtual machine(VM) instances in the networked computing environment that are potentialcandidates for optimization based upon at least one of the following: aperformance of the set of VM instances with respect to a set of servicelevel agreement (SLA) terms, or a commonality of an entity associatedwith the set of VM instances; and optimize the set VM instances byperforming at least one of the following actions: splitting a singleinstance of the set of VM instances into multiple instances, orconsolidating multiple instances of the set of VM instances into asingle instance.
 20. The computer program product of claim 19, thecomputer readable storage media further comprising instructions todetermine whether an actual usage of the set of VM instances is below apredefined threshold as compared to a target usage as set forth in theset of SLA terms.
 21. The computer program product of claim 19, thecomputer readable storage media further comprising instructions tocompare a user identification corresponding to each of the set of VMinstances to one another.
 22. The computer program product of claim 19,the computer readable storage media further comprising instructions to:establish communication between a first instance and a second instanceof the set of VM instances; provide credentials associated with thesecond instance to the first instance; and delete the second instance.23. The computer program product of claim 19 the computer readablestorage media further comprising instructions to: generate, responsiveto an existence of a first instance of the set of VM instances, a secondinstance to correspond to a first instance of the set of VM instances;establish communication between the first instance and the secondinstance; and copy a set of credentials associated the first instance tothe second instance.
 24. The computer program product of claim 19, thecomputer readable storage media further comprising instructions to:update a network configuration associated with the set of VM instances;move a set of services associated with the set of VM instances; update aset of service pointers associated with the set of services; and deletea set of unused resources.
 25. The computer program product of claim 24,the computer readable storage media further comprising instructions tocreate a set of resources in the event the optimizing comprisessplitting.
 26. The computer program product of claim 24, the computerreadable storage media further comprising instructions to: identify theset of services; and determine at least one location to move the set ofservices to.
 27. The computer program product of claim 26, the set ofservices being identified based upon at least one of the following: aminimization of a time needed to perform the identifying, or amaximization of at least one benefit associated with the set of SLAterms.
 28. A method for deploying a system for optimizing virtualmachine instances in a networked computing environment, comprising:providing a computer infrastructure being operable to: identify a set ofvirtual machine (VM) instances in the networked computing environmentthat are potential candidates for optimization based upon at least oneof the following: a performance of the set of VM instances with respectto a set of service level agreement (SLA) terms, or a commonality of anentity associated with the set of VM instances; and optimize the set VMinstances by performing at least one of the following actions: splittinga single instance of the set of VM instances into multiple instances, orconsolidating multiple instances of the set of VM instances into asingle instance.